|submitted by ososru to Bitcoin4free [link] [comments]|
|submitted by Hellterskelt to bitcoin_is_dead [link] [comments]|
|submitted by Rufflenator to 3bitcoins [link] [comments]|
|submitted by dailypriceaction to ForexPriceAction [link] [comments]|
Hi guys,submitted by getmrmarket to Forex [link] [comments]
I have been using reddit for years in my personal life (not trading!) and wanted to give something back in an area where i am an expert.
I worked at an investment bank for seven years and joined them as a graduate FX trader so have lots of professional experience, by which i mean I was trained and paid by a big institution to trade on their behalf. This is very different to being a full-time home trader, although that is not to discredit those guys, who can accumulate a good amount of experience/wisdom through self learning.
When I get time I'm going to write a mid-length posts on each topic for you guys along the lines of how i was trained. I guess there would be 15-20 topics in total so about 50-60 posts. Feel free to comment or ask questions.
The first topic is Risk Management and we'll cover it in three parts
Why it mattersThe first rule of making money through trading is to ensure you do not lose money. Look at any serious hedge fund’s website and they’ll talk about their first priority being “preservation of investor capital.”
You have to keep it before you grow it.
Strangely, if you look at retail trading websites, for every one article on risk management there are probably fifty on trade selection. This is completely the wrong way around.
The great news is that this stuff is pretty simple and process-driven. Anyone can learn and follow best practices.
Seriously, avoiding mistakes is one of the most important things: there's not some holy grail system for finding winning trades, rather a routine and fairly boring set of processes that ensure that you are profitable, despite having plenty of losing trades alongside the winners.
Capital and position sizingThe first thing you have to know is how much capital you are working with. Let’s say you have $100,000 deposited. This is your maximum trading capital. Your trading capital is not the leveraged amount. It is the amount of money you have deposited and can withdraw or lose.
Position sizing is what ensures that a losing streak does not take you out of the market.
A rule of thumb is that one should risk no more than 2% of one’s account balance on an individual trade and no more than 8% of one’s account balance on a specific theme. We’ll look at why that’s a rule of thumb later. For now let’s just accept those numbers and look at examples.
So we have $100,000 in our account. And we wish to buy EURUSD. We should therefore not be risking more than 2% which $2,000.
We look at a technical chart and decide to leave a stop below the monthly low, which is 55 pips below market. We’ll come back to this in a bit. So what should our position size be?
We go to the calculator page, select Position Size and enter our details. There are many such calculators online - just google "Pip calculator".
So the appropriate size is a buy position of 363,636 EURUSD. If it reaches our stop level we know we’ll lose precisely $2,000 or 2% of our capital.
You should be using this calculator (or something similar) on every single trade so that you know your risk.
Now imagine that we have similar bets on EURJPY and EURGBP, which have also broken above moving averages. Clearly this EUR-momentum is a theme. If it works all three bets are likely to pay off. But if it goes wrong we are likely to lose on all three at once. We are going to look at this concept of correlation in more detail later.
The total amount of risk in our portfolio - if all of the trades on this EUR-momentum theme were to hit their stops - should not exceed $8,000 or 8% of total capital. This allows us to go big on themes we like without going bust when the theme does not work.
As we’ll see later, many traders only win on 40-60% of trades. So you have to accept losing trades will be common and ensure you size trades so they cannot ruin you.
Similarly, like poker players, we should risk more on trades we feel confident about and less on trades that seem less compelling. However, this should always be subject to overall position sizing constraints.
For example before you put on each trade you might rate the strength of your conviction in the trade and allocate a position size accordingly:
To keep yourself disciplined you should try to ensure that no more than one in twenty trades are graded exceptional and allocated 5% of account balance risk. It really should be a rare moment when all the stars align for you.
Notice that the nice thing about dealing in percentages is that it scales. Say you start out with $100,000 but end the year up 50% at $150,000. Now a 1% bet will risk $1,500 rather than $1,000. That makes sense as your capital has grown.
It is extremely common for retail accounts to blow-up by making only 4-5 losing trades because they are leveraged at 50:1 and have taken on far too large a position, relative to their account balance.
Consider that GBPUSD tends to move 1% each day. If you have an account balance of $10k then it would be crazy to take a position of $500k (50:1 leveraged). A 1% move on $500k is $5k.
Two perfectly regular down days in a row — or a single day’s move of 2% — and you will receive a margin call from the broker, have the account closed out, and have lost all your money.
Do not let this happen to you. Use position sizing discipline to protect yourself.
Kelly CriterionIf you’re wondering - why “about 2%” per trade? - that’s a fair question. Why not 0.5% or 10% or any other number?
The Kelly Criterion is a formula that was adapted for use in casinos. If you know the odds of winning and the expected pay-off, it tells you how much you should bet in each round.
This is harder than it sounds. Let’s say you could bet on a weighted coin flip, where it lands on heads 60% of the time and tails 40% of the time. The payout is $2 per $1 bet.
Well, absolutely you should bet. The odds are in your favour. But if you have, say, $100 it is less obvious how much you should bet to avoid ruin.
Say you bet $50, the odds that it could land on tails twice in a row are 16%. You could easily be out after the first two flips.
Equally, betting $1 is not going to maximise your advantage. The odds are 60/40 in your favour so only betting $1 is likely too conservative. The Kelly Criterion is a formula that produces the long-run optimal bet size, given the odds.
Applying the formula to forex trading looks like this:
Position size % = Winning trade % - ( (1- Winning trade %) / Risk-reward ratio
If you have recorded hundreds of trades in your journal - see next chapter - you can calculate what this outputs for you specifically.
If you don't have hundreds of trades then let’s assume some realistic defaults of Winning trade % being 30% and Risk-reward ratio being 3. The 3 implies your TP is 3x the distance of your stop from entry e.g. 300 pips take profit and 100 pips stop loss.
So that’s 0.3 - (1 - 0.3) / 3 = 6.6%.
Hold on a second. 6.6% of your account probably feels like a LOT to risk per trade.This is the main observation people have on Kelly: whilst it may optimise the long-run results it doesn’t take into account the pain of drawdowns. It is better thought of as the rational maximum limit. You needn’t go right up to the limit!
With a 30% winning trade ratio, the odds of you losing on four trades in a row is nearly one in four. That would result in a drawdown of nearly a quarter of your starting account balance. Could you really stomach that and put on the fifth trade, cool as ice? Most of us could not.
Accordingly people tend to reduce the bet size. For example, let’s say you know you would feel emotionally affected by losing 25% of your account.
Well, the simplest way is to divide the Kelly output by four. You have effectively hidden 75% of your account balance from Kelly and it is now optimised to avoid a total wipeout of just the 25% it can see.
This gives 6.6% / 4 = 1.65%. Of course different trading approaches and different risk appetites will provide different optimal bet sizes but as a rule of thumb something between 1-2% is appropriate for the style and risk appetite of most retail traders.
Incidentally be very wary of systems or traders who claim high winning trade % like 80%. Invariably these don’t pass a basic sense-check:
How to use stop losses sensiblyStop losses have a bad reputation amongst the retail community but are absolutely essential to risk management. No serious discretionary trader can operate without them.
A stop loss is a resting order, left with the broker, to automatically close your position if it reaches a certain price. For a recap on the various order types visit this chapter.
The valid concern with stop losses is that disreputable brokers look for a concentration of stops and then, when the market is close, whipsaw the price through the stop levels so that the clients ‘stop out’ and sell to the broker at a low rate before the market naturally comes back higher. This is referred to as ‘stop hunting’.
This would be extremely immoral behaviour and the way to guard against it is to use a highly reputable top-tier broker in a well regulated region such as the UK.
Why are stop losses so important? Well, there is no other way to manage risk with certainty.
You should always have a pre-determined stop loss before you put on a trade. Not having one is a recipe for disaster: you will find yourself emotionally attached to the trade as it goes against you and it will be extremely hard to cut the loss. This is a well known behavioural bias that we’ll explore in a later chapter.
Learning to take a loss and move on rationally is a key lesson for new traders.
A common mistake is to think of the market as a personal nemesis. The market, of course, is totally impersonal; it doesn’t care whether you make money or not.
Bruce Kovner, founder of the hedge fund Caxton Associates
There is an old saying amongst bank traders which is “losers average losers”.
It is tempting, having bought EURUSD and seeing it go lower, to buy more. Your average price will improve if you keep buying as it goes lower. If it was cheap before it must be a bargain now, right? Wrong.
Where does that end? Always have a pre-determined cut-off point which limits your risk. A level where you know the reason for the trade was proved ‘wrong’ ... and stick to it strictly. If you trade using discretion, use stops.
Picking a clear levelWhere you leave your stop loss is key.
Typically traders will leave them at big technical levels such as recent highs or lows. For example if EURUSD is trading at 1.1250 and the recent month’s low is 1.1205 then leaving it just below at 1.1200 seems sensible.
If you were going long, just below the double bottom support zone seems like a sensible area to leave a stop
You want to give it a bit of breathing room as we know support zones often get challenged before the price rallies. This is because lots of traders identify the same zones. You won’t be the only one selling around 1.1200.
The “weak hands” who leave their sell stop order at exactly the level are likely to get taken out as the market tests the support. Those who leave it ten or fifteen pips below the level have more breathing room and will survive a quick test of the level before a resumed run-up.
Your timeframe and trading style clearly play a part. Here’s a candlestick chart (one candle is one day) for GBPUSD.
If you are putting on a trend-following trade you expect to hold for weeks then you need to have a stop loss that can withstand the daily noise. Look at the downtrend on the chart. There were plenty of days in which the price rallied 60 pips or more during the wider downtrend.
So having a really tight stop of, say, 25 pips that gets chopped up in noisy short-term moves is not going to work for this kind of trade. You need to use a wider stop and take a smaller position size, determined by the stop level.
There are several tools you can use to help you estimate what is a safe distance and we’ll look at those in the next section.
There are of course exceptions. For example, if you are doing range-break style trading you might have a really tight stop, set just below the previous range high.
Clearly then where you set stops will depend on your trading style as well as your holding horizons and the volatility of each instrument.
Here are some guidelines that can help:
For example if you stop understanding why a product is going up or down and your fundamental thesis has been confirmed wrong, get out. For example, if you are long because you think the central bank is turning hawkish and AUDUSD is going to play catch up with rates … then you hear dovish noises from the central bank and the bond yields retrace lower and back in line with the currency - close your AUDUSD position. You already know your thesis was wrong. No need to give away more money to the market.
Coming up in part IIEDIT: part II here
Letting stops breathe
When to change a stop
Entering and exiting winning positions
Coming up in part IIISqueezes and other risks
Crap trades, timeouts and monthly limits
Disclaimer:This content is not investment advice and you should not place any reliance on it. The views expressed are the author's own and should not be attributed to any other person, including their employer.
Firstly, thanks for the overwhelming comments and feedback. Genuinely really appreciated. I am pleased 500+ of you find it useful.submitted by getmrmarket to Forex [link] [comments]
If you didn't read the first post you can do so here: risk management part I. You'll need to do so in order to make sense of the topic.
As ever please comment/reply below with questions or feedback and I'll do my best to get back to you.
Letting stops breatheWe talked earlier about giving a position enough room to breathe so it is not stopped out in day-to-day noise.
Let’s consider the chart below and imagine you had a trailing stop. It would be super painful to miss out on the wider move just because you left a stop that was too tight.
Imagine being long and stopped out on a meaningless retracement ... ouch!
One simple technique is simply to look at your chosen chart - let’s say daily bars. And then look at previous trends and use the measuring tool. Those generally look something like this and then you just click and drag to measure.
For example if we wanted to bet on a downtrend on the chart above we might look at the biggest retracement on the previous uptrend. That max drawdown was about 100 pips or just under 1%. So you’d want your stop to be able to withstand at least that.
If market conditions have changed - for example if CVIX has risen - and daily ranges are now higher you should incorporate that. If you know a big event is coming up you might think about that, too. The human brain is a remarkable tool and the power of the eye-ball method is not to be dismissed. This is how most discretionary traders do it.
There are also more analytical approaches.
Some look at the Average True Range (ATR). This attempts to capture the volatility of a pair, typically averaged over a number of sessions. It looks at three separate measures and takes the largest reading. Think of this as a moving average of how much a pair moves.
For example, below shows the daily move in EURUSD was around 60 pips before spiking to 140 pips in March. Conditions were clearly far more volatile in March. Accordingly, you would need to leave your stop further away in March and take a correspondingly smaller position size.
ATR is available on pretty much all charting systems
Professional traders tend to use standard deviation as a measure of volatility instead of ATR. There are advantages and disadvantages to both. Averages are useful but can be misleading when regimes switch (see above chart).
Once you have chosen a measure of volatility, stop distance can then be back-tested and optimised. For example does 2x ATR work best or 5x ATR for a given style and time horizon?
Discretionary traders may still eye-ball the ATR or standard deviation to get a feeling for how it has changed over time and what ‘normal’ feels like for a chosen study period - daily, weekly, monthly etc.
Reasons to change a stopAs a general rule you should be disciplined and not change your stops. Remember - losers average losers. This is really hard at first and we’re going to look at that in more detail later.
There are some good reasons to modify stops but they are rare.
One reason is if another risk management process demands you stop trading and close positions. We’ll look at this later. In that case just close out your positions at market and take the loss/gains as they are.
Another is event risk. If you have some big upcoming data like Non Farm Payrolls that you know can move the market +/- 150 pips and you have no edge going into the release then many traders will take off or scale down their positions. They’ll go back into the positions when the data is out and the market has quietened down after fifteen minutes or so. This is a matter of some debate - many traders consider it a coin toss and argue you win some and lose some and it all averages out.
Trailing stops can also be used to ‘lock in’ profits. We looked at those before. As the trade moves in your favour (say up if you are long) the stop loss ratchets with it. This means you may well end up ‘stopping out’ at a profit - as per the below example.
The mighty trailing stop loss order
It is perfectly reasonable to have your stop loss move in the direction of PNL. This is not exposing you to more risk than you originally were comfortable with. It is taking less and less risk as the trade moves in your favour. Trend-followers in particular love trailing stops.
One final question traders ask is what they should do if they get stopped out but still like the trade. Should they try the same trade again a day later for the same reasons? Nope. Look for a different trade rather than getting emotionally wed to the original idea.
Let’s say a particular stock looked cheap based on valuation metrics yesterday, you bought, it went down and you got stopped out. Well, it is going to look even better on those same metrics today. Maybe the market just doesn’t respect value at the moment and is driven by momentum. Wait it out.
Otherwise, why even have a stop in the first place?
Entering and exiting winning positionsTake profits are the opposite of stop losses. They are also resting orders, left with the broker, to automatically close your position if it reaches a certain price.
Imagine I’m long EURUSD at 1.1250. If it hits a previous high of 1.1400 (150 pips higher) I will leave a sell order to take profit and close the position.
The rookie mistake on take profits is to take profit too early. One should start from the assumption that you will win on no more than half of your trades. Therefore you will need to ensure that you win more on the ones that work than you lose on those that don’t.
Sad to say but incredibly common: retail traders often take profits way too early
This is going to be the exact opposite of what your emotions want you to do. We are going to look at that in the Psychology of Trading chapter.
Remember: let winners run. Just like stops you need to know in advance the level where you will close out at a profit. Then let the trade happen. Don’t override yourself and let emotions force you to take a small profit. A classic mistake to avoid.
The trader puts on a trade and it almost stops out before rebounding. As soon as it is slightly in the money they spook and cut out, instead of letting it run to their original take profit. Do not do this.
Entering positions with limit ordersThat covers exiting a position but how about getting into one?
Take profits can also be left speculatively to enter a position. Sometimes referred to as “bids” (buy orders) or “offers” (sell orders). Imagine the price is 1.1250 and the recent low is 1.1205.
You might wish to leave a bid around 1.2010 to enter a long position, if the market reaches that price. This way you don’t need to sit at the computer and wait.
Again, typically traders will use tech analysis to identify attractive levels. Again - other traders will cluster with your orders. Just like the stop loss we need to bake that in.
So this time if we know everyone is going to buy around the recent low of 1.1205 we might leave the take profit bit a little bit above there at 1.1210 to ensure it gets done. Sure it costs 5 more pips but how mad would you be if the low was 1.1207 and then it rallied a hundred points and you didn’t have the trade on?!
There are two more methods that traders often use for entering a position.
Scaling in is one such technique. Let’s imagine that you think we are in a long-term bulltrend for AUDUSD but experiencing a brief retracement. You want to take a total position of 500,000 AUD and don’t have a strong view on the current price action.
You might therefore leave a series of five bids of 100,000. As the price moves lower each one gets hit. The nice thing about scaling in is it reduces pressure on you to pick the perfect level. Of course the risk is that not all your orders get hit before the price moves higher and you have to trade at-market.
Pyramiding is the second technique. Pyramiding is for take profits what a trailing stop loss is to regular stops. It is especially common for momentum traders.
Pyramiding into a position means buying more as it goes in your favour
Again let’s imagine we’re bullish AUDUSD and want to take a position of 500,000 AUD.
Here we add 100,000 when our first signal is reached. Then we add subsequent clips of 100,000 when the trade moves in our favour. We are waiting for confirmation that the move is correct.
Obviously this is quite nice as we humans love trading when it goes in our direction. However, the drawback is obvious: we haven’t had the full amount of risk on from the start of the trend.
You can see the attractions and drawbacks of both approaches. It is best to experiment and choose techniques that work for your own personal psychology as these will be the easiest for you to stick with and build a disciplined process around.
Risk:reward and win ratiosBe extremely skeptical of people who claim to win on 80% of trades. Most traders will win on roughly 50% of trades and lose on 50% of trades. This is why risk management is so important!
Once you start keeping a trading journal you’ll be able to see how the win/loss ratio looks for you. Until then, assume you’re typical and that every other trade will lose money.
If that is the case then you need to be sure you make more on the wins than you lose on the losses. You can see the effect of this below.
A combination of win % and risk:reward ratio determine if you are profitable
A typical rule of thumb is that a ratio of 1:3 works well for most traders.
That is, if you are prepared to risk 100 pips on your stop you should be setting a take profit at a level that would return you 300 pips.
One needn’t be religious about these numbers - 11 pips and 28 pips would be perfectly fine - but they are a guideline.
Again - you should still use technical analysis to find meaningful chart levels for both the stop and take profit. Don’t just blindly take your stop distance and do 3x the pips on the other side as your take profit. Use the ratio to set approximate targets and then look for a relevant resistance or support level in that kind of region.
Risk-adjusted returnsNot all returns are equal. Suppose you are examining the track record of two traders. Now, both have produced a return of 14% over the year. Not bad!
The first trader, however, made hundreds of small bets throughout the year and his cumulative PNL looked like the left image below.
The second trader made just one bet — he sold CADJPY at the start of the year — and his PNL looked like the right image below with lots of large drawdowns and volatility.
Would you rather have the first trading record or the second?
If you were investing money and betting on who would do well next year which would you choose? Of course all sensible people would choose the first trader. Yet if you look only at returns one cannot distinguish between the two. Both are up 14% at that point in time. This is where the Sharpe ratio helps .
A high Sharpe ratio indicates that a portfolio has better risk-adjusted performance. One cannot sensibly compare returns without considering the risk taken to earn that return.
If I can earn 80% of the return of another investor at only 50% of the risk then a rational investor should simply leverage me at 2x and enjoy 160% of the return at the same level of risk.
This is very important in the context of Execution Advisor algorithms (EAs) that are popular in the retail community. You must evaluate historic performance by its risk-adjusted return — not just the nominal return. Incidentally look at the Sharpe ratio of ones that have been live for a year or more ...
Otherwise an EA developer could produce two EAs: the first simply buys at 1000:1 leverage on January 1st ; and the second sells in the same manner. At the end of the year, one of them will be discarded and the other will look incredible. Its risk-adjusted return, however, would be abysmal and the odds of repeated success are similarly poor.
Sharpe ratioThe Sharpe ratio works like this:
You don’t really need to know how to calculate Sharpe ratios. Good trading software will do this for you. It will either be available in the system by default or you can add a plug-in.
VARVAR is another useful measure to help with drawdowns. It stands for Value at Risk. Normally people will use 99% VAR (conservative) or 95% VAR (aggressive). Let’s say you’re long EURUSD and using 95% VAR. The system will look at the historic movement of EURUSD. It might spit out a number of -1.2%.
A 5% VAR of -1.2% tells you you should expect to lose 1.2% on 5% of days, whilst 95% of days should be better than that
This means it is expected that on 5 days out of 100 (hence the 95%) the portfolio will lose 1.2% or more. This can help you manage your capital by taking appropriately sized positions. Typically you would look at VAR across your portfolio of trades rather than trade by trade.
Sharpe ratios and VAR don’t give you the whole picture, though. Legendary fund manager, Howard Marks of Oaktree, notes that, while tools like VAR and Sharpe ratios are helpful and absolutely necessary, the best investors will also overlay their own judgment.
Investors can calculate risk metrics like VaR and Sharpe ratios (we use them at Oaktree; they’re the best tools we have), but they shouldn’t put too much faith in them. The bottom line for me is that risk management should be the responsibility of every participant in the investment process, applying experience, judgment and knowledge of the underlying investments.Howard Marks of Oaktree Capital
What he’s saying is don’t misplace your common sense. Do use these tools as they are helpful. However, you cannot fully rely on them. Both assume a normal distribution of returns. Whereas in real life you get “black swans” - events that should supposedly happen only once every thousand years but which actually seem to happen fairly often.
These outlier events are often referred to as “tail risk”. Don’t make the mistake of saying “well, the model said…” - overlay what the model is telling you with your own common sense and good judgment.
Coming up in part IIIAvailable here
Squeezes and other risks
Crap trades, timeouts and monthly limits
Disclaimer:This content is not investment advice and you should not place any reliance on it. The views expressed are the author's own and should not be attributed to any other person, including their employer.
submitted by Tokenomy to tokenomyofficial [link] [comments]
Author: Christian Hsieh, CEO of Tokenomy
This paper examines some explanations for the continual global market demand for the U.S. dollar, the rise of stablecoins, and the utility and opportunities that crypto dollars can offer to both the cryptocurrency and traditional markets.
The U.S. dollar, dominant in world trade since the establishment of the 1944 Bretton Woods System, is unequivocally the world’s most demanded reserve currency. Today, more than 61% of foreign bank reserves and nearly 40% of the entire world’s debt is denominated in U.S. dollars1.
However, there is a massive supply and demand imbalance in the U.S. dollar market. On the supply side, central banks throughout the world have implemented more than a decade-long accommodative monetary policy since the 2008 global financial crisis. The COVID-19 pandemic further exacerbated the need for central banks to provide necessary liquidity and keep staggering economies moving. While the Federal Reserve leads the effort of “money printing” and stimulus programs, the current money supply still cannot meet the constant high demand for the U.S. dollar2. Let us review some of the reasons for this constant dollar demand from a few economic fundamentals.
Demand for U.S. DollarsFirstly, most of the world’s trade is denominated in U.S. dollars. Chief Economist of the IMF, Gita Gopinath, has compiled data reflecting that the U.S. dollar’s share of invoicing was 4.7 times larger than America’s share of the value of imports, and 3.1 times its share of world exports3. The U.S. dollar is the dominant “invoicing currency” in most developing countries4.
This U.S. dollar preference also directly impacts the world’s debt. According to the Bank of International Settlements, there is over $67 trillion in U.S. dollar denominated debt globally, and borrowing outside of the U.S. accounted for $12.5 trillion in Q1 20205. There is an immense demand for U.S. dollars every year just to service these dollar debts. The annual U.S. dollar buying demand is easily over $1 trillion assuming the borrowing cost is at 1.5% (1 year LIBOR + 1%) per year, a conservative estimate.
Secondly, since the U.S. has a much stronger economy compared to its global peers, a higher return on investments draws U.S. dollar demand from everywhere in the world, to invest in companies both in the public and private markets. The U.S. hosts the largest stock markets in the world with more than $33 trillion in public market capitalization (combined both NYSE and NASDAQ)6. For the private market, North America’s total share is well over 60% of the $6.5 trillion global assets under management across private equity, real assets, and private debt investments7. The demand for higher quality investments extends to the fixed income market as well. As countries like Japan and Switzerland currently have negative-yielding interest rates8, fixed income investors’ quest for yield in the developed economies leads them back to the U.S. debt market. As of July 2020, there are $15 trillion worth of negative-yielding debt securities globally (see chart). In comparison, the positive, low-yielding U.S. debt remains a sound fixed income strategy for conservative investors in uncertain market conditions.
Last, but not least, there are many developing economies experiencing failing monetary policies, where hyperinflation has become a real national disaster. A classic example is Venezuela, where the currency Bolivar became practically worthless as the inflation rate skyrocketed to 10,000,000% in 20199. The recent Beirut port explosion in Lebanon caused a sudden economic meltdown and compounded its already troubled financial market, where inflation has soared to over 112% year on year10. For citizens living in unstable regions such as these, the only reliable store of value is the U.S. dollar. According to the Chainalysis 2020 Geography of Cryptocurrency Report, Venezuela has become one of the most active cryptocurrency trading countries11. The demand for cryptocurrency surges as a flight to safety mentality drives Venezuelans to acquire U.S. dollars to preserve savings that they might otherwise lose. The growth for cryptocurrency activities in those regions is fueled by these desperate citizens using cryptocurrencies as rails to access the U.S. dollar, on top of acquiring actual Bitcoin or other underlying crypto assets.
The Rise of Crypto DollarsDue to the highly volatile nature of cryptocurrencies, USD stablecoin, a crypto-powered blockchain token that pegs its value to the U.S. dollar, was introduced to provide stable dollar exposure in the crypto trading sphere. Tether is the first of its kind. Issued in 2014 on the bitcoin blockchain (Omni layer protocol), under the token symbol USDT, it attempts to provide crypto traders with a stable settlement currency while they trade in and out of various crypto assets. The reason behind the stablecoin creation was to address the inefficient and burdensome aspects of having to move fiat U.S. dollars between the legacy banking system and crypto exchanges. Because one USDT is theoretically backed by one U.S. dollar, traders can use USDT to trade and settle to fiat dollars. It was not until 2017 that the majority of traders seemed to realize Tether’s intended utility and started using it widely. As of April 2019, USDT trading volume started exceeding the trading volume of bitcoina12, and it now dominates the crypto trading sphere with over $50 billion average daily trading volume13.
An interesting aspect of USDT is that although the claimed 1:1 backing with U.S. dollar collateral is in question, and the Tether company is in reality running fractional reserves through a loose offshore corporate structure, Tether’s trading volume and adoption continues to grow rapidly14. Perhaps in comparison to fiat U.S. dollars, which is not really backed by anything, Tether still has cash equivalents in reserves and crypto traders favor its liquidity and convenience over its lack of legitimacy. For those who are concerned about Tether’s solvency, they can now purchase credit default swaps for downside protection15. On the other hand, USDC, the more compliant contender, takes a distant second spot with total coin circulation of $1.8 billion, versus USDT at $14.5 billion (at the time of publication). It is still too early to tell who is the ultimate leader in the stablecoin arena, as more and more stablecoins are launching to offer various functions and supporting mechanisms. There are three main categories of stablecoin: fiat-backed, crypto-collateralized, and non-collateralized algorithm based stablecoins. Most of these are still at an experimental phase, and readers can learn more about them here. With the continuous innovation of stablecoin development, the utility stablecoins provide in the overall crypto market will become more apparent.
Institutional DevelopmentsIn addition to trade settlement, stablecoins can be applied in many other areas. Cross-border payments and remittances is an inefficient market that desperately needs innovation. In 2020, the average cost of sending money across the world is around 7%16, and it takes days to settle. The World Bank aims to reduce remittance fees to 3% by 2030. With the implementation of blockchain technology, this cost could be further reduced close to zero.
J.P. Morgan, the largest bank in the U.S., has created an Interbank Information Network (IIN) with 416 global Institutions to transform the speed of payment flows through its own JPM Coin, another type of crypto dollar17. Although people argue that JPM Coin is not considered a cryptocurrency as it cannot trade openly on a public blockchain, it is by far the largest scale experiment with all the institutional participants trading within the “permissioned” blockchain. It might be more accurate to refer to it as the use of distributed ledger technology (DLT) instead of “blockchain” in this context. Nevertheless, we should keep in mind that as J.P. Morgan currently moves $6 trillion U.S. dollars per day18, the scale of this experiment would create a considerable impact in the international payment and remittance market if it were successful. Potentially the day will come when regulated crypto exchanges become participants of IIN, and the link between public and private crypto assets can be instantly connected, unlocking greater possibilities in blockchain applications.
Many central banks are also in talks about developing their own central bank digital currency (CBDC). Although this idea was not new, the discussion was brought to the forefront due to Facebook’s aggressive Libra project announcement in June 2019 and the public attention that followed. As of July 2020, at least 36 central banks have published some sort of CBDC framework. While each nation has a slightly different motivation behind its currency digitization initiative, ranging from payment safety, transaction efficiency, easy monetary implementation, or financial inclusion, these central banks are committed to deploying a new digital payment infrastructure. When it comes to the technical architectures, research from BIS indicates that most of the current proofs-of-concept tend to be based upon distributed ledger technology (permissioned blockchain)19.
These institutional experiments are laying an essential foundation for an improved global payment infrastructure, where instant and frictionless cross-border settlements can take place with minimal costs. Of course, the interoperability of private DLT tokens and public blockchain stablecoins has yet to be explored, but the innovation with both public and private blockchain efforts could eventually merge. This was highlighted recently by the Governor of the Bank of England who stated that “stablecoins and CBDC could sit alongside each other20”. One thing for certain is that crypto dollars (or other fiat-linked digital currencies) are going to play a significant role in our future economy.
Future OpportunitiesThere is never a dull moment in the crypto sector. The industry narratives constantly shift as innovation continues to evolve. Twelve years since its inception, Bitcoin has evolved from an abstract subject to a familiar concept. Its role as a secured, scarce, decentralized digital store of value has continued to gain acceptance, and it is well on its way to becoming an investable asset class as a portfolio hedge against asset price inflation and fiat currency depreciation. Stablecoins have proven to be useful as proxy dollars in the crypto world, similar to how dollars are essential in the traditional world. It is only a matter of time before stablecoins or private digital tokens dominate the cross-border payments and global remittances industry.
There are no shortages of hypes and experiments that draw new participants into the crypto space, such as smart contracts, new blockchains, ICOs, tokenization of things, or the most recent trends on DeFi tokens. These projects highlight the possibilities for a much more robust digital future, but the market also needs time to test and adopt. A reliable digital payment infrastructure must be built first in order to allow these experiments to flourish.
In this paper we examined the historical background and economic reasons for the U.S. dollar’s dominance in the world, and the probable conclusion is that the demand for U.S. dollars will likely continue, especially in the middle of a global pandemic, accompanied by a worldwide economic slowdown. The current monetary system is far from perfect, but there are no better alternatives for replacement at least in the near term. Incremental improvements are being made in both the public and private sectors, and stablecoins have a definite role to play in both the traditional and the new crypto world.
 How the US dollar became the world’s reserve currency, Investopedia
 The dollar is in high demand, prone to dangerous appreciation, The Economist
 Dollar dominance in trade and finance, Gita Gopinath
 Global trades dependence on dollars, The Economist & IMF working papers
 Total credit to non-bank borrowers by currency of denomination, BIS
 Biggest stock exchanges in the world, Business Insider
 McKinsey Global Private Market Review 2020, McKinsey & Company
 Central banks current interest rates, Global Rates
 Venezuela hyperinflation hits 10 million percent, CNBC
 Lebanon inflation crisis, Reuters
 Venezuela cryptocurrency market, Chainalysis
 The most used cryptocurrency isn’t Bitcoin, Bloomberg
 Trading volume of all crypto assets, coinmarketcap.com
 Tether US dollar peg is no longer credible, Forbes
 New crypto derivatives let you bet on (or against) Tether’s solvency, Coindesk
 Remittance Price Worldwide, The World Bank
 Interbank Information Network, J.P. Morgan
 Jamie Dimon interview, CBS News
 Rise of the central bank digital currency, BIS
 Speech by Andrew Bailey, 3 September 2020, Bank of England
submitted by Eva_Canares to FTMO_Forex_Trading [link] [comments]
Stop-Loss and the Hunger For New Capital
Ever wonder why when you trade your stop gets tagged? Although you put it in a spot where "There's no way price will want to reach my stop level for sure this time"
As a trader, particularly a new trader – I've always wondered why my stops were only tagged for the price of running briefly the area that I've ever so carefully researched ... hit my stop point ..... then move on in the direction of my original study and run to the point where my profit should have been taken.
Everything leaving me wondering ...... In the hell for what did this do??? Obviously this is a common issue that has plagued most traders. At least, I know that I have faced this very problem for years.
What I noticed was that there was a very distinctive pattern going on, and it was repeating itself again and again. I noticed that the traditional supply and demand theory, support and resistance zones, or double top / double bottom trading patterns that I have been told time and time again that price has always covered these regions, was not really a real thing.
The argument had been, ..... Put me into the shoes of the major investment banks vs. the home-trading fighter who was going to conquer the markets every day. If you were a large company with an infinite supply of money and you decided to bring a massive chunk of it into the game, you can't just dump the whole lot into the game and demand all your orders to be filled out at once, then take off the price in the direction you want .... no ..... That is not exactly the way it operates.All these major organizations need to do is pair orders.
And they match that order by sending the markets to areas where liquidity is high .... The stops AKA!
Let 's say you 're evaluating the markets, for example, and deciding that price wants to go higher than an old regular target as it's in a bullish uptrend at the moment. And you see price for the past day, or so, not willing to go any lower.
What looks like a bit of a demand shelf or support level where the demand is all in a nice tight clustered row that just doesn't seem to want to go down and you know for sure this time price won't go under that heavily protected area ..... only for the price to run down quickly and refuse to go up (in this case a long position).
And I started to note that these "secure zones" or places where price is certainly not going to come up / down to be simply used by these large entities as feeding grounds for harvesting liquidity and adding more positions to include them in a larger movement.
They need a lot of money to buy in and just to do so, your sell stop is great. Many traders put their stops below this tight pack range of candles a few pips / ticks / cents believing they 're secure as price obviously doesn't want to come down below them. And most traders have their positions liquidated by the hungry major capital banks to feed the whole push higher than you were originally right about.
And how can you stop this pitfall happening to you is the million-dollar question? There are a few ways to handle this and keep your hard-earned money from being ripped away from you in an moment, which you have at risk in the markets.
Stop-Hunting and the Hunger For New Capital
I found that you would do much better in your trading career if you look at these areas (in the above example a long position) as a chance rather than a safe zone to put your stop. What I mean by that is, anticipate them coming down under those equal lows and try to get far below it instead of getting long above the area of consolidation. Yeah, that means you're going to have to go long when the competition runs against you and I know , I know, it feels really uncomfortable and wrong and goes against all you've been taught ... but believe me that this approach can give you the very best possible entries.
Imagine: getting into the day 's low and riding price action all the way up to the top of everyday scale!!! Wouldn't this be terrific?
Well, if your quantitative skills are timely and your business research tells you to go a long way, then all you need to do is wait for the perfect entry. Let the price build up and create "demand shelf" or support areas for that. Let the market shift sideways and bounce around like a pinball mocking all the other traders who were at the top of these stuff for a long time and put their stops just below them in hopes that the price would not come down and stop them. All the while playing with and holding their emotions on the cliff of –Will this be a winner, or a trade loser? So when price does the unimaginable and runs below the support area and scoops up all the traders stops you can then go long and take part in the glorious upside of being right – and of course make some money doing it.
Notice facile? Well, that is not so. It takes patience and timing and experience to catch all those eager participants who keep their stops on a silver platter for the fat and thirsty banks to suck them up, as the markets normally send price south of the border.
Stop-Loss and the Hunger For New Capital (meme)
You have to define the times of the day when the wrong move is made apparent.
Or when they make that low of the day – typically within the 1st 1 – 4 hours
of the trading day, and I don't mean either when the banks come online at 8 a.m. NY.
I mean 12 am, at the beginning of the day.
So yes you 're definitely going to have to be awake if you like watching
price do its thing and don't trust the process of buying into those down candles.
And use a limit order like me-then go to sleep and trust your overall analysis to be right and wake up to your morning with a nice little start.
But the trick is-where are you going to shop under the lows?
And where does your stop then go when you buy?
Those are all interesting questions that I should seek to answer clearly here – but alas, all markets are different.
Yet general rule of thumb as follows:
However if that is the case then try to turn your power back.
You don't need to make every trade worth a million dollars.
This is about continuity, when dealing, not winning the draw.
I am not recommending trade in these types of trades against the trend.
You need to be in full agreement with the direction of the total daily level.
And bringing it in.
Also, a great way to place the maximum risk reward for your take profit:
Attempt to position it in places above the market where short-sellers will stop.
And in a nutshell, with a bit of analysis, all the knowledge I described above can be readily found, I didn't come up with it on my own and these ideas are not unique. Yet how you adapt them to your particular trading style is up to you and relies on your interpretation of these principles for your success and/or failure. Price is fractal and would want to return to markets it has previously sold before – if you accept the basic fact you ought to be doing very well in your business career.
Eva " Forex " Canares .
Cheers and Profitable Trading to All.
About FTMO -
They fund forex traders. Just Pass their risk management rules and begin trading for their company. They'll provide you capital up to $300k USD for trading the financial markets. 70% of profits you keep and losses are covered by them. How does it work?
How to Become a Funded Forex ,Stocks or CryptoCurrency Trader?
﷽submitted by aibnsamin1 to Bitcoin [link] [comments]
The Federal Reserve and the United States government are pumping extreme amounts of money into the economy, already totaling over $484 billion. They are doing so because it already had a goal to inflate the United States Dollar (USD) so that the market can continue to all-time highs. It has always had this goal. They do not care how much inflation goes up by now as we are going into a depression with the potential to totally crash the US economy forever. They believe the only way to save the market from going to zero or negative values is to inflate it so much that it cannot possibly crash that low. Even if the market does not dip that low, inflation serves the interest of powerful people.
The impending crash of the stock market has ramifications for Bitcoin, as, though there is no direct ongoing-correlation between the two, major movements in traditional markets will necessarily affect Bitcoin. According to the Blockchain Center’s Cryptocurrency Correlation Tool, Bitcoin is not correlated with the stock market. However, when major market movements occur, they send ripples throughout the financial ecosystem which necessary affect even ordinarily uncorrelated assets.
Therefore, Bitcoin will reach X price on X date after crashing to a price of X by X date.
Stock Market CrashThe Federal Reserve has caused some serious consternation with their release of ridiculous amounts of money in an attempt to buoy the economy. At face value, it does not seem to have any rationale or logic behind it other than keeping the economy afloat long enough for individuals to profit financially and politically. However, there is an underlying basis to what is going on which is important to understand in order to profit financially.
All markets are functionally price probing systems. They constantly undergo a price-discovery process. In a fiat system, money is an illusory and a fundamentally synthetic instrument with no intrinsic value – similar to Bitcoin. The primary difference between Bitcoin is the underlying technology which provides a slew of benefits that fiat does not. Fiat, however, has an advantage in being able to have the support of powerful nation-states which can use their might to insure the currency’s prosperity.
Traditional stock markets are composed of indices (pl. of index). Indices are non-trading market instruments which are essentially summaries of business values which comprise them. They are continuously recalculated throughout a trading day, and sometimes reflected through tradable instruments such as Exchange Traded Funds or Futures. Indices are weighted by market capitalizations of various businesses.
Price theory essentially states that when a market fails to take out a new low in a given range, it will have an objective to take out the high. When a market fails to take out a new high, it has an objective to make a new low. This is why price-time charts go up and down, as it does this on a second-by-second, minute-by-minute, day-by-day, and even century-by-century basis. Therefore, market indices will always return to some type of bull market as, once a true low is formed, the market will have a price objective to take out a new high outside of its’ given range – which is an all-time high. Instruments can only functionally fall to zero, whereas they can grow infinitely.
So, why inflate the economy so much?
Deflation is disastrous for central banks and markets as it raises the possibility of producing an overall price objective of zero or negative values. Therefore, under a fractional reserve system with a fiat currency managed by a central bank – the goal of the central bank is to depreciate the currency. The dollar is manipulated constantly with the intention of depreciating its’ value.
Central banks have a goal of continued inflated fiat values. They tend to ordinarily contain it at less than ten percent (10%) per annum in order for the psyche of the general populace to slowly adjust price increases. As such, the markets are divorced from any other logic. Economic policy is the maintenance of human egos, not catering to fundamental analysis. Gross Domestic Product (GDP) growth is well-known not to be a measure of actual growth or output. It is a measure of increase in dollars processed. Banks seek to produce raising numbers which make society feel like it is growing economically, making people optimistic. To do so, the currency is inflated, though inflation itself does not actually increase growth. When society is optimistic, it spends and engages in business – resulting in actual growth. It also encourages people to take on credit and debts, creating more fictional fiat.
Inflation is necessary for markets to continue to reach new heights, generating positive emotional responses from the populace, encouraging spending, encouraging debt intake, further inflating the currency, and increasing the sale of government bonds. The fiat system only survives by generating more imaginary money on a regular basis.
Bitcoin investors may profit from this by realizing that stock investors as a whole always stand to profit from the market so long as it is managed by a central bank and does not collapse entirely. If those elements are filled, it has an unending price objective to raise to new heights. It also allows us to realize that this response indicates that the higher-ups believe that the economy could crash in entirety, and it may be wise for investors to have multiple well-thought-out exit strategies.
Economic Analysis of BitcoinThe reason why the Fed is so aggressively inflating the economy is due to fears that it will collapse forever or never rebound. As such, coupled with a global depression, a huge demand will appear for a reserve currency which is fundamentally different than the previous system. Bitcoin, though a currency or asset, is also a market. It also undergoes a constant price-probing process. Unlike traditional markets, Bitcoin has the exact opposite goal. Bitcoin seeks to appreciate in value and not depreciate. This has a quite different affect in that Bitcoin could potentially become worthless and have a price objective of zero.
Bitcoin was created in 2008 by a now famous mysterious figure known as Satoshi Nakamoto and its’ open source code was released in 2009. It was the first decentralized cryptocurrency to utilize a novel protocol known as the blockchain. Up to one megabyte of data may be sent with each transaction. It is decentralized, anonymous, transparent, easy to set-up, and provides myriad other benefits. Bitcoin is not backed up by anything other than its’ own technology.
Bitcoin is can never be expected to collapse as a framework, even were it to become worthless. The stock market has the potential to collapse in entirety, whereas, as long as the internet exists, Bitcoin will be a functional system with a self-authenticating framework. That capacity to persist regardless of the actual price of Bitcoin and the deflationary nature of Bitcoin means that it has something which fiat does not – inherent value.
Bitcoin is based on a distributed database known as the “blockchain.” Blockchains are essentially decentralized virtual ledger books, replete with pages known as “blocks.” Each page in a ledger is composed of paragraph entries, which are the actual transactions in the block.
Blockchains store information in the form of numerical transactions, which are just numbers. We can consider these numbers digital assets, such as Bitcoin. The data in a blockchain is immutable and recorded only by consensus-based algorithms. Bitcoin is cryptographic and all transactions are direct, without intermediary, peer-to-peer.
Bitcoin does not require trust in a central bank. It requires trust on the technology behind it, which is open-source and may be evaluated by anyone at any time. Furthermore, it is impossible to manipulate as doing so would require all of the nodes in the network to be hacked at once – unlike the stock market which is manipulated by the government and “Market Makers”. Bitcoin is also private in that, though the ledge is openly distributed, it is encrypted. Bitcoin’s blockchain has one of the greatest redundancy and information disaster recovery systems ever developed.
Bitcoin has a distributed governance model in that it is controlled by its’ users. There is no need to trust a payment processor or bank, or even to pay fees to such entities. There are also no third-party fees for transaction processing. As the ledge is immutable and transparent it is never possible to change it – the data on the blockchain is permanent. The system is not easily susceptible to attacks as it is widely distributed. Furthermore, as users of Bitcoin have their private keys assigned to their transactions, they are virtually impossible to fake. No lengthy verification, reconciliation, nor clearing process exists with Bitcoin.
Bitcoin is based on a proof-of-work algorithm. Every transaction on the network has an associated mathetical “puzzle”. Computers known as miners compete to solve the complex cryptographic hash algorithm that comprises that puzzle. The solution is proof that the miner engaged in sufficient work. The puzzle is known as a nonce, a number used only once. There is only one major nonce at a time and it issues 12.5 Bitcoin. Once it is solved, the fact that the nonce has been solved is made public.
A block is mined on average of once every ten minutes. However, the blockchain checks every 2,016,000 minutes (approximately four years) if 201,600 blocks were mined. If it was faster, it increases difficulty by half, thereby deflating Bitcoin. If it was slower, it decreases, thereby inflating Bitcoin. It will continue to do this until zero Bitcoin are issued, projected at the year 2140. On the twelfth of May, 2020, the blockchain will halve the amount of Bitcoin issued when each nonce is guessed. When Bitcoin was first created, fifty were issued per block as a reward to miners. 6.25 BTC will be issued from that point on once each nonce is solved.
Unlike fiat, Bitcoin is a deflationary currency. As BTC becomes scarcer, demand for it will increase, also raising the price. In this, BTC is similar to gold. It is predictable in its’ output, unlike the USD, as it is based on a programmed supply. We can predict BTC’s deflation and inflation almost exactly, if not exactly. Only 21 million BTC will ever be produced, unless the entire network concedes to change the protocol – which is highly unlikely.
Some of the drawbacks to BTC include congestion. At peak congestion, it may take an entire day to process a Bitcoin transaction as only three to five transactions may be processed per second. Receiving priority on a payment may cost up to the equivalent of twenty dollars ($20). Bitcoin mining consumes enough energy in one day to power a single-family home for an entire week.
Trading or Investing?The fundamental divide in trading revolves around the question of market structure. Many feel that the market operates totally randomly and its’ behavior cannot be predicted. For the purposes of this article, we will assume that the market has a structure, but that that structure is not perfect. That market structure naturally generates chart patterns as the market records prices in time. In order to determine when the stock market will crash, causing a major decline in BTC price, we will analyze an instrument, an exchange traded fund, which represents an index, as opposed to a particular stock. The price patterns of the various stocks in an index are effectively smoothed out. In doing so, a more technical picture arises. Perhaps the most popular of these is the SPDR S&P Standard and Poor 500 Exchange Traded Fund ($SPY).
In trading, little to no concern is given about value of underlying asset. We are concerned primarily about liquidity and trading ranges, which are the amount of value fluctuating on a short-term basis, as measured by volatility-implied trading ranges. Fundamental analysis plays a role, however markets often do not react to real-world factors in a logical fashion. Therefore, fundamental analysis is more appropriate for long-term investing.
The fundamental derivatives of a chart are time (x-axis) and price (y-axis). The primary technical indicator is price, as everything else is lagging in the past. Price represents current asking price and incorrectly implementing positions based on price is one of the biggest trading errors.
Markets and currencies ordinarily have noise, their tendency to back-and-fill, which must be filtered out for true pattern recognition. That noise does have a utility, however, in allowing traders second chances to enter favorable positions at slightly less favorable entry points. When you have any market with enough liquidity for historical data to record a pattern, then a structure can be divined. The market probes prices as part of an ongoing price-discovery process. Market technicians must sometimes look outside of the technical realm and use visual inspection to ascertain the relevance of certain patterns, using a qualitative eye that recognizes the underlying quantitative nature
Markets and instruments rise slower than they correct, however they rise much more than they fall. In the same vein, instruments can only fall to having no worth, whereas they could theoretically grow infinitely and have continued to grow over time. Money in a fiat system is illusory. It is a fundamentally synthetic instrument which has no intrinsic value. Hence, the recent seemingly illogical fluctuations in the market.
According to trade theory, the unending purpose of a market or instrument is to create and break price ranges according to the laws of supply and demand. We must determine when to trade based on each market inflection point as defined in price and in time as opposed to abandoning the trend (as the contrarian trading in this sub often does). Time and Price symmetry must be used to be in accordance with the trend. When coupled with a favorable risk to reward ratio, the ability to stay in the market for most of the defined time period, and adherence to risk management rules; the trader has a solid methodology for achieving considerable gains.
We will engage in a longer term market-oriented analysis to avoid any time-focused pressure. The Bitcoin market is open twenty-four-hours a day, so trading may be done when the individual is ready, without any pressing need to be constantly alert. Let alone, we can safely project months in advance with relatively high accuracy. Bitcoin is an asset which an individual can both trade and invest, however this article will be focused on trading due to the wide volatility in BTC prices over the short-term.
Technical Indicator Analysis of BitcoinTechnical indicators are often considered self-fulfilling prophecies due to mass-market psychology gravitating towards certain common numbers yielded from them. They are also often discounted when it comes to BTC. That means a trader must be especially aware of these numbers as they can prognosticate market movements. Often, they are meaningless in the larger picture of things.
Trend Definition Analysis of BitcoinTrend definition is highly powerful, cannot be understated. Knowledge of trend logic is enough to be a profitable trader, yet defining a trend is an arduous process. Multiple trends coexist across multiple time frames and across multiple market sectors. Like time structure, it makes the underlying price of the instrument irrelevant. Trend definitions cannot determine the validity of newly formed discretes. Trend becomes apparent when trades based in counter-trend inflection points continue to fail.
Downtrends are defined as an instrument making lower lows and lower highs that are recurrent, additive, qualified swing setups. Downtrends for all instruments are similar, except forex. They are fast and complete much quicker than uptrends. An average downtrend is 18 months, something which we will return to. An uptrend inception occurs when an instrument reaches a point where it fails to make a new low, then that low will be tested. After that, the instrument will either have a deep range retracement or it may take out the low slightly, resulting in a double-bottom. A swing must eventually form.
A simple way to roughly determine trend is to attempt to draw a line from three tops going upwards (uptrend) or a line from three bottoms going downwards (downtrend). It is not possible to correctly draw a downtrend line on the BTC chart, but it is possible to correctly draw an uptrend – indicating that the overall trend is downwards. The only mitigating factor is the impending stock market crash.
Time Symmetry Analysis of BitcoinTime is the movement from the past through the present into the future. It is a measurement in quantified intervals. In many ways, our perception of it is a human construct. It is more powerful than price as time may be utilized for a trade regardless of the market inflection point’s price. Were it possible to perfectly understand time, price would be totally irrelevant due to the predictive certainty time affords. Time structure is easier to learn than price, but much more difficult to apply with any accuracy. It is the hardest aspect of trading to learn, but also the most rewarding.
Humans do not have the ability to recognize every time window, however the ability to define market inflection points in terms of time is the single most powerful trading edge. Regardless, price should not be abandoned for time alone. Time structure analysis It is inherently flawed, as such the markets have a fail-safe, which is Price Structure. Even though Time is much more powerful, Price Structure should never be completely ignored. Time is the qualifier for Price and vice versa. Time can fail by tricking traders into counter-trend trading.
Time is a predestined trade quantifier, a filter to slow trades down, as it allows a trader to specifically focus on specific time windows and rest at others. It allows for quantitative measurements to reach deterministic values and is the primary qualifier for trends. Time structure should be utilized before price structure, and it is the primary trade criterion which requires support from price. We can see price structure on a chart, as areas of mathematical support or resistance, but we cannot see time structure.
Time may be used to tell us an exact point in the future where the market will inflect, after Price Theory has been fulfilled. In the present, price objectives based on price theory added to possible future times for market inflection points give us the exact time of market inflection points and price.
Time Structure is repetitions of time or inherent cycles of time, occurring in a methodical way to provide time windows which may be utilized for inflection points. They are not easily recognized and not easily defined by a price chart as measuring and observing time is very exact. Time structure is not a science, yet it does require precise measurements. Nothing is certain or definite. The critical question must be if a particular approach to time structure is currently lucrative or not.
We will measure it in intervals of 180 bars. Our goal is to determine time windows, when the market will react and when we should pay the most attention. By using time repetitions, the fact that market inflection points occurred at some point in the past and should, therefore, reoccur at some point in the future, we should obtain confidence as to when SPY will reach a market inflection point. Time repetitions are essentially the market’s memory. However, simply measuring the time between two points then trying to extrapolate into the future does not work. Measuring time is not the same as defining time repetitions. We will evaluate past sessions for market inflection points, whether discretes, qualified swings, or intra-range. Then records the times that the market has made highs or lows in a comparable time period to the future one seeks to trade in.
What follows is a time Histogram – A grouping of times which appear close together, then segregated based on that closeness. Time is aligned into combined histogram of repetitions and cycles, however cycles are irrelevant on a daily basis. If trading on an hourly basis, do not use hours.
Evaluating the yearly lows, we see that BTC tends to have its lows primarily at the beginning of every year, with a possibility of it being at the end of the year. Following the same methodology, we get the middle of the month as the likeliest day. However, evaluating the monthly lows for the past year, the beginning and end of the month are more likely for lows.
Therefore, we have two primary dates from our histogram.
1/1/21, 1/15/21, and 1/29/21
2:00am, 8:00am, 12:00pm, or 10:00pm
In fact, the high for this year was February the 14th, only thirty days off from our histogram calculations.
The 8.6-Year Armstrong-Princeton Global Economic Confidence model states that 2.15 year intervals occur between corrections, relevant highs and lows. 2.15 years from the all-time peak discrete is February 9, 2020 – a reasonably accurate depiction of the low for this year (which was on 3/12/20). (Taking only the Armstrong model into account, the next high should be Saturday, April 23, 2022). Therefore, the Armstrong model indicates that we have actually bottomed out for the year!
Bear markets cannot exist in perpetuity whereas bull markets can. Bear markets will eventually have price objectives of zero, whereas bull markets can increase to infinity. It can occur for individual market instruments, but not markets as a whole. Since bull markets are defined by low volatility, they also last longer. Once a bull market is indicated, the trader can remain in a long position until a new high is reached, then switch to shorts. The average bear market is eighteen months long, giving us a date of August 19th, 2021 for the end of this bear market – roughly speaking. They cannot be shorter than fifteen months for a central-bank controlled market, which does not apply to Bitcoin. (Otherwise, it would continue until Sunday, September 12, 2021.) However, we should expect Bitcoin to experience its’ exponential growth after the stock market re-enters a bull market.
Terry Laundy’s T-Theory implemented by measuring the time of an indicator from peak to trough, then using that to define a future time window. It is similar to an head-and-shoulders pattern in that it is the process of forming the right side from a synthetic technical indicator. If the indicator is making continued lows, then time is recalculated for defining the right side of the T. The date of the market inflection point may be a price or indicator inflection date, so it is not always exactly useful. It is better to make us aware of possible market inflection points, clustered with other data. It gives us an RSI low of May, 9th 2020.
The Bradley Cycle is coupled with volatility allows start dates for campaigns or put options as insurance in portfolios for stocks. However, it is also useful for predicting market moves instead of terminal dates for discretes. Using dates which correspond to discretes, we can see how those dates correspond with changes in VIX.
Therefore, our timeline looks like:
submitted by FmzQuant to CryptoCurrencyTrading [link] [comments]
SummaryIn the previous article, we explained the premise of realizing the trading strategy from the aspects of the introduction of the M language , the basic grammar, the model execution method, and the model classification. In this article, we will continue the previous part, from the commonly used strategy modules and technologies. Indicators, step by step to help you achieve a viable intraday quantitative trading strategy.
Stage IncreaseStage increase is calculating the percentage of current K line's closing price compare with previous N periods of closing price's difference. For example: Computing the latest 10 K-lines stage increases, can be written:
CLOSE_0:=CLOSE; //get the current K-line's closing price, and save the results to variable CLOSE_0. CLOSE_10:=REF(CLOSE,10); //get the pervious 10 K-lines' closing price, and save the results to variable CLOSE_10 (CLOSE_0-CLOSE_10)/CLOSE_10*100;//calculating the percentage of current K line's closing price compare with previous N periods of closing price's difference.
New high priceThe new high price is calculated by whether the current K line is greater than N cycles' highest price. For example: calculating whether the current K line is greater than the latest 10 K-lines' highest price, can be written:
HHV_10:=HHV(HIGH,10); //Get the highest price of latest 10 K-lines, which includes the current K-line. HIGH>REF(HHV_10,1); //Judge whether the current K-line's highest price is greater than pervious K-lines' HHV_10 value.
Price raise with massive trading volume increaseFor example: If the current K line's closing price is 1.5 times of the closing price of the previous 10 K-lines, which means in 10 days, the price has risen 50%; and the trading volume also increased more than 5 times of the pervious 10 K-lines. can be written:
CLOSE_10:=REF(CLOSE,10); //get the 10th K-line closing price IS_CLOSE:=CLOSE/CLOSE_10>1.5; //Judging whether the current K Line closing price is 1.5 times greater than the value of CLOSE_10 VOL_MA_10:=MA(VOL,10); //get the latest 10 K-lines' average trading volume IS_VOL:=VOL>VOL_MA_10*5; //Judging whether the current K-line's trading volume is 5 times greater than the value of VOL_MA_10 IS_CLOSE AND IS_VOL; //Judging whether the condition of IS_CLOSE and IS_VOL are both true.
Price narrow-shock marketNarrow-shock market means that the price is maintained within a certain range in the recent period. For example: If the highest price in 10 cycles minus the lowest price in 10 cycles, the result divided by the current K-line's closing price is less than 0.05. can be written:
HHV_10:=HHV(CLOSE,10); //Get the highest price in 10 cycles(including current K-line) LLV_10:=LLV(CLOSE,10); //Get the lowest price in 10 cycles(including current K-line) (HHV_10-LLV_10)/CLOSE<0.05; //Judging whether the difference between HHV_10 and LLV_10 divided by current k-line's closing price is less than 0.05.
Moving average indicates bull marketMoving Average indicates long and short direction, K line supported by or resisted by 5，10，20，30，60 moving average line, Moving average indicates bull market or bear market. can be written:
MA_5:=MA(CLOSE,5); //get the moving average of 5 cycle closing price. MA_10:=MA(CLOSE,10);//get the moving average of 10 cycle closing price. MA_20:=MA(CLOSE,20);//get the moving average of 20 cycle closing price. MA_30:=MA(CLOSE,30);//get the moving average of 30 cycle closing price. MA_5>MA_10 AND MA_10>MA_20 AND MA_20>MA_30; //determine wether the MA_5 is greater than MA_10, and MA_10 is greater than MA_20, and MA_20 is greater than MA_30.
Previous high price and its locationsTo obtain the location of the previous high price and its location, you can use FMZ Quant API directly. can be written:
HHV_20:=HHV(HIGH,20); //get the highest price of 20 cycle(including current K line) HHVBARS_20:=HHVBARS(HIGH,20); //get the number of cycles from the highest price in 20 cycles to current K line HHV_60_40:REF(HHV_20,40); //get the highest price between 60 cycles and 40 cycles.
Price gap jumpingThe price gap is the case where the highest and lowest prices of the two K lines are not connected. It consists of two K lines, and the price gap is the reference price of the support and pressure points in the future price movement. When a price gap occurs, it can be assumed that an acceleration along the trend with original direction has begun. can be written:
HHV_1:=REF(H,1); //get the pervious K line's highest price LLV_1:=REF(L,1); //get the pervious K line's lowest price HH:=L>HHV_1; //judging wether the current K line's lowest price is greater than pervious K line's highest price (jump up) LL:=H
Common technical indicatorsMoving average
From a statistical point of view, the moving average is the arithmetic average of the daily price, which is a trending price trajectory. The moving average system is a common technical tool used by most analysts. From a technical point of view, it is a factor that affects the psychological price of technical analysts. The decision-making factor of thinking trading is a good reference tool for technical analysts. The FMZ Quant tool supports many different types of moving averages, as shown below:
MA_DEMO:MA(CLOSE,5); // get the moving average of 5 cycle MA_DEMO:EMA(CLOSE,15); // get the smooth moving average of 15 cycle MA_DEMO:EMA2(CLOSE,10);// get the linear weighted moving average of 10 cycle MA_DEMO:EMAWH(CLOSE,50); // get the exponentially weighted moving average of 50 cycle MA_DEMO:DMA(CLOSE,100); // get the dynamic moving average of 100 cycle MA_DEMO:SMA(CLOSE,10,3); // get the fixed weight of 3 moving average of closing price in 10 cycle MA_DEMO:ADMA(CLOSE,9,2,30); // get the fast-line 2 and slow-line 30 Kaufman moving average of closing price in 9 cycle.
Bollinger bands is also based on the statistical principle. The middle rail is calculated according to the N-day moving average, and the upper and lower rails are calculated according to the standard deviation. When the BOLL channel starts changing from wide to narrow, which means the price will gradually returns to the mean. When the BOLL channel is changing from narrow to wide, it means that the market will start to change. If the price is up cross the upper rail, it means that the buying power is enhanced. If the price down cross the lower rail, it indicates that the selling power is enhanced.
Among all the technical indicators, Bollinger Bands calculation method is one of the most complicated, which introduces the concept of standard deviation in statistics, involving the middle trajectory ( MB ), the upper trajectory ( UP ) and the lower trajectory ( DN ). luckily, you don't have to know the calculation details, you can use it directly on FMZ Quant platform as follows:
MID:MA(CLOSE,100); //calculating moving average of 100 cycle, call it Bollinger Bands middle trajectory TMP2:=STD(CLOSE,100); //calculating standard deviation of closing price of 100 cycle. TOP:MID+2*TMP2; //calculating middle trajectory plus 2 times of standard deviation, call it upper trajectory BOTTOM:MID-2*TMP2; //calculating middle trajectory plus 2 times of standard deviation, call it lower trajectory
The MACD indicator is a double smoothing operation using fast (short-term) and slow (long-term) moving averages and their aggregation and separation. The MACD developed according to the principle of moving averages removes the defect that the moving average frequently emits false signals, and also retains the effect of the other good aspect. Therefore, the MACD indicator has the trend and stability of the moving average. It was used to study the timing of buying and selling stocks and predicts stock price change. You can use it as follows:
DIFF:EMA(CLOSE,10)-EMA(CLOSE,50); //First calculating the difference between short-term moving average and long-term moving average. DEA:EMA(DIFF,10); //Then calculating average of the difference.The above is the commonly used strategy module in the development of quantitative trading strategies. In addition, there are far more than that. Through the above module examples, you can also implement several trading modules that you use most frequently in subjective trading. The methods are the same. Next, we began to write a viable intraday trading strategy.
Strategy WritingIn the Forex spot market, there is a wellknown strategy called HANS123. Its logic are basically judging wether the price breaks through the highest or lowest price of the number of K lines after the market opening
// Data Calculation Q:=BARSLAST(DATA<>REF(DATA,1))+1; //Calculating the number of period from the first K line of the current trading day to current k line, and assign the results to N HH:=VALUEWHEN(TIME=0930,HHV(H,Q)); //when time is 9:30, get the highest price of N cycles, and assign the results to HH LL:=VALUEWHEN(TIME=0930,LLV(L,Q)); //When time is 9:30, get the lowest price of N cycles, and assign the results to LL //Placing Orders TIME>0930 AND TIME<1445 AND C>HH,BK; //If the time is greater than 9:30 and lesser than 14:45, and the closing price is greater than HH, opening long position. TIME>0930 AND TIME<1445 AND C
To sum upAbove we have learned the concept of the strategy module. Through several commonly used strategy module cases, we had a general idea of the FMZ Quant programming tools, it can be said that learning to write strategy modules and improve programming logic thinking is a key step in advanced quantitative trading. Finally, we used the FMZ Quant tool to implement the trading strategy according a classical Forex trading strategy.
Next section noticeMaybe there are still some confusion for some people, mainly because of the coding part. Don't worry, we have already thought of that for you. On the FMZ Quant platform, there is another even easier programming tool for beginners. It is the visual programming, let's learn it soon!
The table of average daily range for 28 currency pairs from 2014 to 2020. (the numbers are rounded) Average Daily Range of Gold (XAUUSD) was added to the table. For Average Daily Range of Exotic Forex pairs see here. Update on June, 2020 The GBP/JPY is still one of the most popular pairs amongst traders with an average daily trading range of 141 pips, but the GBP/USD and USD/CAD are both good markets to day trade or swing trade with a daily movement in excess of 100 pips, and the EUR/JPY and AUD/USD are also fairly volatile right now as well. Forex Average Daily Range Strategy Example. Now let’s look at an example ADR trading strategy. In the image below you will see a chart with the daily ADR indicator. This is the H1 chart of the USD/CHF Forex pair for Dec 13 – 14, 2016. The image shows the ADR indicator values at the top left corner. The ADR is adjusted to take into ... The average daily range is one of those concepts that truly captivates traders. People imagine the amazing possibilities that they will be able to create using this tool in their trading. Average Daily Trading Range of the Major Forex Pairs in 2019 January 30, 2019 by James Woolley 2 Comments If you are day trading the forex markets, it is important that you trade those currency pairs that have tight spreads first of all, but it is also a good idea to trade the more volatile pairs that have large average trading ranges every day ...
[index]          
How to trade Forex Using Average Daily Range - Duration: 3:07. Forex Source 1,147 views. 3:07. Trade Setup Using Average Daily Price Range - Duration: 9:08. trader2B Proprietary trading 3,840 views. And another one of course, like you said is the ADR or the Average Daily Range. ... you’ll love Forex Source. There’s a link below were you can learn more about it https://bit.ly/2HFykNd ... The daily range of movements in forex pairs is different. Some currency pairs move larger and have a bigger pip movement than others on average and are more ... Check Out More FREE Forex Training Videos Here: http://www.compassfx.com/video Forex Trading With Average Daily Range And Median Price Levels Pt 1 - Duration: 17:01. Stacey Burke Trading 2,195 views. 17:01. Average Daily Range Trading Techniques - Duration: 8:40.